TF1.x vs TF2.0 Pioneering lirary for building deep learning models, launch November 2015. Its free, open source, originally developed by Google. Other libraries: PyTorch – from FB, October 2016 TensorFlow 2.0 Major new version, September 2019 Dynamoic computation graphs Not backward compatible with TF1 Closer to PyTorch TF1.x vs TF2.0 vs PyTorch TF1.x PyTorch Computation […]
Model Evaluation – Regression
Model Evaluation Techniques This notebook will only deal with commonly used evaluation metrics for regression and classification. This list is not exhaustive, you are encouraged to look at the other metrics that can be used. References: (1) Scikit-Learn : https://scikit-learn.org/stable/modules/model_evaluation.html (2) https://github.com/maykulkarni/Machine-Learning-Notebooks Useful Resources : https://scikit-learn.org/stable/modules/model_evaluation.html https://scikit-learn.org/stable/modules/model_evaluation.html#mean-absolute-error In [1]: import numpy as np import matplotlib.pyplot as […]
Model Evaluation – Classification
Model Evaluation Techniques This notebook will only deal with commonly used evaluation metrics for classification. This list is not exhaustive, you are encouraged to look at the other metrics that can be used. References: (1) Scikit-Learn : https://scikit-learn.org/stable/modules/model_evaluation.html (2) https://github.com/maykulkarni/Machine-Learning-Notebooks Useful Resources : https://scikit-learn.org/stable/modules/model_evaluation.html https://scikit-learn.org/stable/modules/model_evaluation.html#mean-absolute-error In [1]: import numpy as np import matplotlib.pyplot as plt import […]
Machine Learning – Regression Algorithms
Machine learning Algorithms using Scikit-Learn Ref : All the documentation for the functions used can be found at https://scikit-learn.org/stable/ This notebook aims to introduce you to the scikit-learn library that contains a lot of popularly used Machine Learning algorithms. This notebook contains the following section: (1) Regression Each section has a data preparation section […]
Machine Learning Algorithms Scikit-Learn
Machine learning Algorithms using Scikit-Learn Ref : All the documentation for the functions used can be found at https://scikit-learn.org/stable/ This notebook aims to introduce you to the scikit-learn library that contains a lot of popularly used Machine Learning algorithms. This notebook contains the following section: (1) Classification For the classification component, we use the […]
Python Panda Data Visualization
Data Operations using Python and Pandas Using Python to prepare data for Machine Learning tasks and other data analysis¶ This notebook has been taken from the following link. Please follow that link to find more such notebooks on different topics. Ref : https://sebastianraschka.com/notebooks/python-notebooks.html This notebook explores pandas and matplotlib (library for visualization) by analyzing a […]
Python Pandas
Introduction to Pandas library with Python This notebook has been taken from the following link. Please follow that link to find more such notebooks on different topics. Ref : https://sebastianraschka.com/notebooks/python-notebooks.html Pandas is a popular library compatible with python, for Machine Learning and Data Analysis. This notebook aims to introduce you to a couple of basic […]
Python Introduction including Numpy
Python Numpy Tutorial This is notebook is part of the CS231n (Convolutional Neural Networks for Visual Recognition) offered at Stanford University. Introduction Python is a great general-purpose programming language on its own, but with the help of a few popular libraries (numpy, scipy, matplotlib) it becomes a powerful environment for scientific computing. We expect that […]
Machine Learning Overview
Machine Learning = building a model from example inputs to make data-driven predictions vs following strictly static program instructions. Traditional programming contains logic that the machine must follow to execution. Machine Learning does not have same logic like traditional if, loops, case etc. Instead, it is based on data and some given algorithm. With that […]